Mina Alibeigi

In this talk, we will explore the critical role of comprehensive and varied driving data in the development of reliable and effective autonomous driving technology. A key focus will be on the Zenseact Open Dataset (ZOD), a large, diverse, multimodal dataset recently released to propel autonomous driving advancements. We will delve into the unique features of ZOD, outlining how it was created and the measures taken for its public release. This release aims to spur innovation in the field, pushing forward robust and safe autonomous driving while enhancing overall road safety. Additionally, the talk will briefly highlight our recent and ongoing research projects, showcasing how ZOD is being utilized in various potential applications.

Mina Alibeigi is an experienced AI research lead and scientist focused on contributing to the advancement of autonomous driving (AD) technology. Holding a Ph.D. in Robotics and Machine Intelligence, her contributions to the AI community are reflected in several real-world AI system implementations, patent applications, and scientific publications. In her role as an AD researcher at Zenseact, Mina leads projects like Zenseact Open Dataset. Additionally, as a visiting researcher at Cambridge Machine Learning Systems Lab, Mina delves into large-scale decentralized learning. Beyond her technical role, she actively shares knowledge in various forums, engages in talks, and advocates for the next generation’s empowerment at events like “Women in AI” and “Girls in Tech.”